A Neural Network for Sensor Hybridization in Rocket Guidance

Celis, Raúl de; Solano-López, Pablo; Cadarso, Luís

doi:10.1109/wsc48552.2020.9384129

Cited by 1 publication

(1 citation statement)

References 22 publications

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“…Due to its advantages of being high resolution, fast response, and low cost [1][2][3], it has become a popular non-contact measurement instrument. Therefore, it is widely used in laser guidance [4], laser tracking [5], sub-nanometer measurements [6], space laser communication [7], and synchronous optical position detection [8], as well as in other fields.…”

Section: Introductionmentioning

confidence: 99%

High-Precision Log-Ratio Spot Position Detection Algorithm with a Quadrant Detector under Different SNR Environments

Huo

et al. 2022

Sensors

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In atmospheric laser communication, a beam is transmitted through an atmospheric channel, and the photocurrent output from a quadrant detector (QD) used as the tracking sensor fluctuates significantly. To ensure uninterrupted communication and to adapt to such fluctuations, in this paper we apply logarithmic amplifiers to process the output signals of a QD. To further improve the measurement accuracy of the spot position, we firstly propose an integral infinite log-ratio algorithm (IILRA) and an integral infinity log-ratio algorithm based on the signal-to-noise ratio (BSNR-IILRA) through analysis of the factors influencing the measurement error considering the signal-to-noise ratio (SNR) parameter. Secondly, the measurement error of the two algorithms under different SNRs and their variations are analyzed. Finally, a spot position detection experiment platform is built to correctly and efficiently verify the two algorithms. The experimental results show that when the SNR is 54.10 dB, the maximum error and root mean square error of the spot position of the IILRA are 0.0054 mm and 0.0039 mm, respectively, which are less than half those of the center approximation algorithm (CAA). When the SNR is 23.88 dB, the maximum error and root mean square error of the spot position of the BSNR-IILRA are 0.0046 mm and 0.0034 mm, respectively, which are one-thirtieth and one-twentieth of the CAA, respectively. The spot position measurement accuracy of the two proposed algorithms is significantly improved compared with the CAA.

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Section: Introductionmentioning

confidence: 99%

High-Precision Log-Ratio Spot Position Detection Algorithm with a Quadrant Detector under Different SNR Environments

Huo

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

A Neural Network for Sensor Hybridization in Rocket Guidance

Cited by 1 publication

References 22 publications

High-Precision Log-Ratio Spot Position Detection Algorithm with a Quadrant Detector under Different SNR Environments

High-Precision Log-Ratio Spot Position Detection Algorithm with a Quadrant Detector under Different SNR Environments

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